Odgovornost bez podrške: fenomenološko istraživanje hrvatskog akademskog sustava

This paper examines the paradox of “responsibility without support” in contemporary Croatian academia: researchers are increasingly required to demonstrate transparency, measurability, and social impact, while the collegial and institutional conditions that would enable such responsibility are simultaneously eroding. The theoretical framework connects Whitley’s typology of “strong” and “weak” research evaluation systems with the distinction between enabling and constraining structures of academic work, as well as debates on plural regimes of valuation and epistemic living spaces. Empirically, the study is based on a phenomenological interpretation of 24 in-depth interviews with researchers from the natural, technical, social, and biomedical sciences. The findings point to a threefold tension: (1) between the inner ethics of scientific work and external evaluative demands, (2) between the need for trust and logic of surveillance, and (3) between intrinsic scientific values and extrinsic metrics. Responsibility is internalized as a moral imperative accompanied by a pronounced emotional cost—guilt, exhaustion, and ambivalence—yet it simultaneously gives rise to micro-practices of resilience, such as mentor-ship, pedagogical relations, collaboration, and the cultivation of curiosity. The paper makes three main contributions: it conceptualizes responsibility without support as a diagnostic category within the moral economy of science; it connects macro-level evaluation policies with micro-level experiences through the concept of epistemic living spaces; and, based on the interpretation of the findings, it discusses implications for the recalibration of research evaluation systems, including the pluralization of criteria, administrative relief, the institutionalization of care, and the development of stable channels of dialogue. While the study is limited by its qualitative, interpretative design and the specificity of the current reform context, it offers high analytical transferability, with patterns that are recognizable across other “strong” evaluation regimes.